Efficient market hypothesis

Efficient market hypothesis Introduction: From the last several decades the efficiency of stock market has been the sole purpose of research studies. As a result, several theories have been introduced and implemented in relation to principally how the competition in the stock market will force the known information into the prices of securities. The knowledge of information on a variety of securities that are traded in the market is one of the major factors in influencing the movements of stock market. In the stock market, a securities price tends to move rise and fall depending mainly on the availability of the information. The stock prices in the efficient market correspond to available information and therefore register any rise or fall mainly when recent and unpredictable information is available. The up and down in the security prices largely depends upon the advantages and disadvantages associated with the available information and to what extent it will affect the companys performance which is represented by the secur ity. As it is very difficult to tell whether the information available is useful or not, in the same way it is quite impossible to make predictions about the trend of the stock market, such that whether there will be an upward or downward trend in the near future by using the available information. In the financial market it is not mandatory that all professionals related to market always possess the information about the securities and have skills to evaluate this information for their gain. The only thing the efficient market requires is that few individuals must have the information about securities and as a result of the information supplied by them, the whole market must be well informed and benefitted. Hence the available information plays an important role in determining the efficiency of the stock market. By focussing on the above idea, the concept of Efficient Market Hypothesis has been developed and became one of the most concentrated and debatable topic among professionals and people related to finance and stock market studies. RESEARCH AIM: The main aim of my research is to analyse the efficiency of stock market supported by the concept of Efficient Market Hypothesis. It also aims to depict the impact of the Efficient Market Hypothesis on security trading by reviewing the available literature. RESEARCH QUESTIONS: My research aims to answer the following questions: To what extent the available information, according to the concept of Efficient Market Theory, affects the security trading in stock market. What is insider trading and its impact on the efficiency of stock market. What are the various types of anomalies associated with the stock market and their effect on the stock market efficiency. LITERATURE REVIEW: In this part of my research paper I will re-examine the existing literature on the anomalies and the efficiency of the stock market. An efficient market is defined as a market where there are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value.(Eugene F. Fama 1965) According to the Efficient Market Hypothesis, given by Fama, the ups and downs in the prices of securities in the financial market totally reflect known information at a specified period of time. In other words, Efficient Market Hypothesis states that the trading of securities by the individuals is always carried out purely based on the assumption that securities worth are always more or less than the price offer by market. Whereas, trading of securities trying to outperform the stock market will be luck instead of professional skills if current prices fully reflect all available information as well as stock markets are efficient. According to this hypothesis if new information is revealed about a firm it will be incorporated into the share price rapidly and rationally, with respect to the direction of the share price movement and the size of that movement. (Elearn -NetTel) . Efficiency is an unclear word in itself so for more clarification, in my dissertation, I will describe all ty pes of efficiencies: operational, allocation and pricing. I will also give full detail on levels of market efficiency : weak-form efficiency, semi-strong form efficiency and strong-form efficiency. According Random walk theory , there are no trends and format that are being followed by the prices of securities in stock market. There is another fact given by this theory which says that the prices of securities in the past can not be useful for future predictions and fluctuation in prices. The Efficient Market Hypothesis and anomalies related to the stock market developed by the researchers always contrasts with each other. The search for anomalies is effectively the search for systems or patterns that can be used to outperform passive and/or buy-and-hold strategies. (Invest Home). With the invention of any anomaly, there is always a kind of exploitation by the investors of the anomalies discovered in order to increase their profit. This practice make the anomaly disappear with the passage of time. There are so many internal and external factors of the entities that affects the operations of stock market and those factors are often known as Anomalies which plays an important role in over performing or under performing the operations of the stock market by taking into consideration the fact that these anomalies have good or bad effect on the prices of stocks and entities. There are different types of anomalies and some of the anomalies are discussed. Fundamental Anomalies: First type of anomaly is fundamental anomaly which basically depends upon the price of the stock and on the past performance of the entity due to which stock prices rises or fall. Several anomalies of these kinds exist related to the growth, present value and profitability of the companies concerned. Under fundamental anomaly, there exist a most historical and famous anomaly named Value investing and is regarded as the most appropriate strategy for investment purposes. These anomalies depend on the stock value and companys performance based on which the stock prices go up or down. A technique used is to divide the given index into high price and low price to book value stocks. The low price to book concept was developed by Eugene Fama and Keneth French favouring the hypothesis that lower risk is attached to value stocks whereas the stocks with growth are attached with higher risk. According to another anomaly named as low price to sales, stocks with low price to sales ratio perform b etter then high price to sales ratio. According to James P. O Shaughnesey, prices are the only strongest determinant of excessive return. There are several studies which advocates that stocks having low P/E ratio always perform better in the market as compared to stocks with high P/E ratios. In the same manner, the stocks with high dividend yield are better performers than stocks with low dividend yields. There are some other stocks named as neglected stock and are chosen by those with the contrarian strategy. A study was conducted by F.M DeBondtand Richard Thaler on 35 best and worst performer stocks between 1932 and 1977 in New York Stock Exchange and came out with the result that the performance of best performer stocks in the stock exchange falls whereas the stocks with bad performance in the past showed better results when compared to the results of the same stock in the past. Technical Anomalies: Another types of anomalies in which past prices and statistics are used to predict the prices of securities are known as technical anomalies. The techniques used in these types of anomalies include strategies related to support and resistance, moving averages and strength. Some researchers are against the method of technical analysis and say that the investors are hardly benefitted from these technical analysis techniques where as some researchers argue that there is enough evidence and facts that are sufficient to say that the technical analysis method is favourable for the investors. According to technical analysts, the selling of stocks is influenced by the resistance level whereas the buying is influenced at the support level. A signal to sell the stock is developed in case the support level is penetrated by the price whereas a signal to buy the stock is produced in case price penetrated the resistance level. According to the conclusion made by William Brock, Josef Lakonishok, an d Blake LeBaron, the outcomes are reliable with technical rules having forecasting power. But at the same time the cost related to transaction must be taken into account before implementing such concepts and strategies. Another conclusion given by them says that the stock returns generating is more complicated and different process as compared to the results obtained by conducting different studies and researches using various linear models. Calendar Anomalies: Calendar anomaly is another type of anomaly in which various effects are included. In January effect, general and small stocks perform abnormally better in the month of January. Philippe Jorion and Robert Haugen say that, the January effect is, perhaps the best-known example of anomalous behaviour in security markets throughout the world. An interesting fact about January effect is that it lasted for nearly two decades whereas any anomaly hardly survive as traders start taking advantage of the anomalies which results in vanishing of anomaly. Another effect named Turn of the Month was founded by Chris R. Hensel and William T. Ziemba, according to which, in between period 1928 to 1993, the returns for the turn of the month performed well and considerably greater than normal performance. According to study, those investors who make regular purchases may be benefitted if they make schedule to do the purchasing at the end and prior to the starting of next month. In addition to these effec ts another effect is known as Monday effect and is considered to be the worst day in stock market if investments are made on this day. According to study conducted by Lawrence Harris, the week end effect occurs during first 45 minutes of buying and selling whereas prices shows upward trend during the first 45 minutes of trading on all other days. This kind of anomaly may occur due to moods and behaviour of people after weekend holidays. Other Anomalies There are certain other facts that are responsible for affecting the operations of stock market. The size effect, announcement based effect, IPOs, Stock buybacks, insider transactions and S and P game. According to Fama and French (1992), the book to market ratio as well as the size capture the cross-sectional variation of average stock returns in NYSE, and Nsdaq securities. A complete investigation of book to market was provided by Tim Loughran in relation to dimensions of firm size, exchange listings etc and experimental findings of French and Fama are basically forwarded by two features of the data which includes relatively low returns on small, new and growing stocks. Srinivas Nippani, Augustine C. Arize study three main US corporate bond market indices by taking into account calendar based anomalies between the years 1982-2002. In the analysis, the whole bond market as well as two broad classes of industries namely industrials and utilities were taken into account. The study find the mixed response for the weekend effect in the overall bond index and industrial index whereas very less response to utilities index. The findings showed definite proof of January effect on the bond market. RESEARCH METHOD AND DATA: Data Collection Methods: The general idea of business research is that it is concerned with collection of data, making questionnaires and then analysing and evaluating the collected data. In addition to this, the identification of problem and the approach needed to solve the problem is also important. (Ghauri et al., 1995). Data sources are often referred to as the carriers of data information. Basically data sources are divided into two categories namely primary data and secondary data. Primary data is concerned with the interviews and observations collected while conducting research project where as, secondary data is collected by others and academic and non academic sources are included in this type of data. In my topic of research which is to study the efficiency of stock market, I want to use the Desk method that is secondary data collection method. This includes the gathering of information from sources like books, journals related to my topic of research, and from electronic media like internet which is one of the major sources of information. These all sources of information will be helpful for the accomplishment of my research. DATA SOURCES: As I have already describe that I will use secondary method in my dissertation so I have to search a lot for this topic and for this search my main resource is FBES (Faculty of Business, Environment and Society) which provides the best online business information services which is also including the digital management library. Some of the main sources (journal databases) for my research area are given below: EBSCO Business Source. Business Source Premiere. Emerald. Science Direct. NetLibrary. Overall these cover hundreds of journals, and give access to up to a million journal articles. EXPECTED OUTCOMES: While reviewing all the information from available literature on efficient market hypothesis, operations of stock market, price fluctuations and the anomalies of stock market, I have come to the conclusion that the following outcomes could be possible and predictable from my research, If the stock market is efficient then no information can play any role in making any change towards the performance of stock market. The efficient market hypothesis is expected to take any of the following forms which are weak, semi-strong and strong which purely depends upon the availability, and trueness of the past and present information about the stock concerned in the stock market. The anomalies like technical anomalies could be of great help to the researchers and analysts to predict the changing trend in the prices of stocks in the stock market but the transaction cost is the cause of concern while using such technical method. There are some other stock market anomalies which purely depend upon the internal and external factors of the entity and may result in fluctuations in the stock market. The anomalies related to stock market exist for short period of time but function against the concept of efficient market hypothesis and in my research I will find out the facts relating to the vibrations in the stock market as a result of these anomalies. LIMITATIONS AND EXPECTED DIFFICULTIES: While conducting my research I have to face certain difficulties and limitations which may occur during the course of my research. As my research involves the collection of secondary data, I have to be quite aware of the limitations that may arise due to the nature of data. Some of the limitations that are possible are as follows It could be possible that the theory and data we collected for our research is unclear and is not helpful for the companies in their decision making. It is important to check the source of the information as it could be wrong and misleading. It is possible that the theory is quite old for studies and research purposes in todays rapidly developing world. The theory may not be fit for application due to development of new and technological methods and techniques used for the analysis. REFERENCES: Chris R. Hensel and William T. Ziemba (1996)Investment Results from Exploiting Turn-of-the-Month Effects, Journal of Portfolio Management 22, 17-23 Elearn NetTel Financial Analysis Revised: Session 1: Market Efficiency [Online] Available From: http://cbdd.wsu.edu/kewlcontent/cdoutput/TR505r/page4.htm Eugene Fama and Kenneth R. French (1992)The Cross-section of Expected Stock Returns, The Journal of Finance 47, 427-465. Eugene F. Fama (1995) Random Walks in Stock Market Prices, Financial Analysts Journal 21, 55-59. Ghauri, P., Gronhaug K and Kristianslund I., (1995) Research methods in business studies a practical guide Hempstead: Prentice Hall Investor Home Historical Stock Market Anomolies [Online] Available From: James P. OShaughnessy (1998) 2nd edn. What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time. New York: McGraw Hills Lawrence Harris (1986) A Transaction Data Study of Weekly and Intradaily Patterns in Stock Returns, Journal of Financial Economics 16, 99-117 Loughran Tim (1997)Book-to-Market across firm Size, Exchange, and seasonality: Is There an Effect? Journal of Finance Quantitative Analysis 32, 249-268 Marc R. Reinganum (1997) The Size Effect: Evidence and Potential Explanations, Investing in Small-Cap and Microcap Securities, Association for Investment Management and Research, 1997. Robert Haugen and Philippe Jorion, (1996)The January Effect: Still There after All These Years, Financial Analysts Journal, January-February 1996. Srinivas Nippani and Anita K. Pennathur (2004) Day-of-the-week effects in commercial paper yield rates. Quaterly Review of economics Finance 44, 508-520 Werner F.M. DeBondtand Richard Thaler (1985)Does the Stock Market Overreact? The Journal of Finance 40, 793-805. Efficient Market Hypothesis Efficient Market Hypothesis Literature Review 2.0 Introduction In order to better understand the origin and the idea behind the Efficient Market Hypothesis (EMH), the first section deals with an overview of the EMH. Section 2 deals with the Random Walk Model which is a close counterpart of the EMH. We then have examine the different degrees of information efficiency that exist, namely the weak form efficiency, semi-strong form efficiency and the strong form efficiency. In section 4, we have a brief overview of the different types of statistical tests that have been used in the literature to examine the weak form efficiency. Section 5 explains the implications of efficient markets for investors. 2.1 Efficient Market Hypothesis (EMH) The concept of efficiency is one of the essential concepts in finance. Market efficiency is a term used in many different contexts with many different meanings. Market efficiency involves three related concepts- allocation efficiency, operational efficiency and informational efficiency. Allocation efficiency: A characteristic of an efficient market in which capital is allocated in a way that benefits all participants. It occurs when organizations in the public and private sectors can obtain funding for the projects that will be the most profitable, thereby promoting economic growth Operational efficiency: A marketcondition that exists when participants can execute transactions and receive services at a price that fairly equates to the actual costs required to provide them.Economists use this term to describe the way resources are employed to facilitate the operation of the market. It is usually desirable that markets carry out their operations at as low a cost as possible. Information efficiency: The actual market price of a share should reflect its intrinsic value. Information efficiency implies that the observed market price of a security reflect all information relevant to the pricing of the security. The investor can manage to earn merely a risk-adjusted return from his investment, as prices move instantaneously and in an unbiased manner to any news. The efficiency in the market for financial assets and assets returns refers here to the information efficiency and should not be confused with the other types of efficiency. As explained by Rahman and Hossain (2006): For a stock market to be efficient, stock prices must always fully reflect all relevant and available information. This definition can be expressed as Æ’(Ri,t, Rj,t à ¢Ã¢â€š ¬Ã‚ ¦ à ¢Ã¢â€š ¬Ã‚ ¦ à ¢Ã¢â€š ¬Ã‚ ¦ | à Ã¢â‚¬  M t-1) = Æ’( Ri,t, Rj,t à ¢Ã¢â€š ¬Ã‚ ¦ à ¢Ã¢â€š ¬Ã‚ ¦ à ¢Ã¢â€š ¬Ã‚ ¦ | à Ã¢â‚¬  M t-1, à Ã¢â‚¬  a t-1), where Æ’(.) = a probability distribution function, Ri,t = the return on security i in period t, à Ã¢â‚¬  M t-1 = the information set used by the market at t à ¢Ã¢â€š ¬Ã¢â‚¬Å" 1, à Ã¢â‚¬  a t-1 = the specific information item placed in the public domain at t à ¢Ã¢â€š ¬Ã¢â‚¬Å" 1. This equation has two important implications. 1. Specific information item at t-1 (à Ã¢â‚¬  a t-1) cannot be used to earn non zero abnormal return. 2. When a new information item is added to the information set à Ã¢â‚¬  M, it is instantaneously reflected on market prices. The concept of market efficiency was first introduced by Bachelier (1900). Since then, there has been many studies like Working (1934), Cowles and Jones (1937), Kendall (1953), Cootner (1964). However it was Fama (1965) who first used termed it as à ¢Ã¢â€š ¬Ã…“efficient marketà ¢Ã¢â€š ¬Ã‚ . Fama (1970) later stated the sufficient but not necessary conditions for efficiency: i. there are no transaction costs in trading securities; ii. all available information is costlessly available to all market participants, and iii. all agree on the implications of current information for the current price and distributions of future prices of each security He also identified three degrees of informational efficiency namely the weak form, the semi-strong form and the strong form. 2.2 Random Walk Model (RWM) The Random Walk Model is a close counterpart of the Efficient Market Hypothesis. The model was originally examined by Kendall (1953). It states that stock price fluctuations are independent of each other and have the same probability distribution. Thus the Random Walk theory suggests that stock price change randomly, making it impossible to predict stock prices. The Random Walk Model is linked to the belief that markets are efficient and that investors cannot beat or predict the market because stock prices reflect all available information and the new information arises randomly. As mentioned in Fama (1970) the two hypotheses constituting the Random Walk Model , that is (i) successive price changes are independent and (ii) successive changes are identically distributed, are implicitly assumed in the Efficient Market Hypothesis. The Random Walk Model is in direct opposition to technical analysis, which suggests that a stocks future price can be forecasted based on historical information through observing chart patterns and technical indicators. 2.3 Forms of Market Efficiency 2.3.1 Weak-Form Efficiency Fama (1970) stipulates that no investor can earn excess returns by formulating trading strategies based on historical price or return information in a weak-form efficient market. The weak-form efficiency thus assumes that the price of a stock fully reflects all information contained in past prices, that is the historical sequence of prices, rate of returns and other historical market information. A weak-form efficient market implies that it is of no use to engage in technical analysis that use past prices alone to find undervalued stocks. In order to test whether past share prices can be used to predict future share prices( that is, weak-form efficiency), statistical or econometric tests can be used. These studies seek to study the evolution of share prices from one period to the next period and try to detect correlation between the successive price changes. Technical analysts study the evolution of past share prices, with the aim of predicting share prices to make gains. 2.3.2 Semi-Strong Form Efficiency Fama (1970) described the semi-strong form efficiency as one where share price fully reflect all information contained not only in past prices but all public information. All public information includes capital market information as used in the weak form Efficient Market Hypothesis(EMH) as well as non-market information such as earnings, dividend announcements, price earnings ratio, information about the economy and political news (Reilly1997). New public information is almost instantaneously integrated in share price and the share price is adjusted so as to reflect the true value of the share. This means that an investor cannot use public information to generate gains on the stock market. In order to test for semi-strong form efficiency, event studies are often used. These event studies are performed by analyzing the effect of the release of new public information on the share price. If the market is semi-strong form efficient, the new public information ( for example annual reports, earning announcement or dividend announcement) is instantaneously integrated in the share price, so as to reflect the intrinsic value of the share. New information can be both good or bad. Thus they can cause increases or decreases at their release. 2.3.3 Strong Form Efficiency Under strong form efficiency, the current price reflects all information, public as well as private. Private information, in this context, means information not yet published. On the stock market, there are professionals (for example security analysts, fund managers) who have private as well as public information. Efficient Market Hypothesis (EMH) assumes that no investor has monopolistic access to any information. This means that as new public and private information is released, it is incorporated in share price to reflect its true value. An investor will not be able to consistently find undervalued or overvalued shares and make gains on the strong form efficient market. Fama (1970) perceives a strong form efficient market as one where investors are not expected to earn excess returns by relying on inside information. To test whether past share prices, public and private information can used to predict future share prices, the investment records and gains generated by professional investors are often studied. Investors should not be consistently able to make gains by using public and private information. At all moments, the share prices incorporate all public and private information to reflect the true value of the shares. 2.4 Statistical Tests to examine validity of Weak-Form EMH In order to examine the validity of the weak form efficiency, a number of statistical tests have been used in the literature. These tests can be categorized into two groups: i. Using mechanical trading rules also known as filter rules. These rules test for the possibility of non-linear dependence existing in the price data. Filter rules were first used by S.A Alexander (1961) and later Fama and Blume (1966) added to the literature. Professor Alexanders filter techniques attempts to apply a sophisticated criteria to identify movements in stock prices. An x percent filter is defined as follows: If the daily closing price of a particular security moves up at least x percent, buy and hold the security until its price moves down at least x percent from a subsequent high, then sell and go short (Fama and Blume, 1966). The short position is then maintained until the daily closing price rises at least x percent above a subsequent low when one is going to cover and buy. Moves less than x percent in either direction are ignored. ii. Statistical tests of independence between successive price changes. Serial autocorrelation tests and run tests are among the most popular tests. Some of the researches in this field use Spectral Analysis which decomposes a time series into a spectrum of cycles of different length. This spectral decomposition of a time series yield a spectral density function that measures the contribution of each of the frequency bands to the overall variance of the times series. There is also a relatively new test introduced by Lo and Mackinlay (1988), it is called the Variance Ratio which is based on the heteroscedasticity problem. The basic idea behind the Lo and Mackinlay (1988) variance-ratios test is that if a natural logarithm of a time series is a pure random walk, then, the variance of its k-differences in a finite sample grows linearly with the difference, Let (pt) denote a time series consisting of T observations p1,p2,à ¢Ã¢â€š ¬Ã‚ ¦,pT of asset returns. Then, the variance-ratio of the k-th difference, VR(k), is defined as: VR(k)= à Ã†â€™2(k)/à Ã†â€™2(1) where, VR(k) is the variance-ratio of the shares returns k-th differences; à Ã†â€™2(k) is the unbiased estimator of 1/k of the variance of the shares returns k-th differences, under the null hypothesis; à Ã†â€™2(1) is the variance of the first-differenced share returns series, and k is the number of days of base observations interval or lag (Ntim et al. ,2007). 2.5 Implications of EMH Market efficiency has important implications for both investors and authorities. If a market is inefficient, investors should doubt the à ¢Ã¢â€š ¬Ã…“hold the marketà ¢Ã¢â€š ¬Ã‚  strategy and should try to à ¢Ã¢â€š ¬Ã…“beat the marketà ¢Ã¢â€š ¬Ã‚ . While the authorities on their part should restructure the stock market by enacting effective law and enhancing financial media. The graph below shows the effect of EMH on stock prices. The straight line shows the reaction under EMH while the dotted lines show the over-reaction and under-reaction that occur with the existence of market imperfections. If a market is efficient, investors: 1. should not worry about investment analysis. They should rather concentrate on holding a well diversified portfolio. Investors holding an inefficient diversified portfolio will be exposed to risk which could be avoided and for which they will not be rewarded. In other words, the market only provides return for systematic risk, while specific risks have to be diversified away. 2. Should adopt a buy and hold policy once they have established their portfolios. This is because there is no advantage in changing from one group of securities to another. By doing this, there would be transaction costs which they would have to incur and as a result, the risk-adjusted return would be affected. Altering the composition of a portfolio can only be justified a) if the risk exposure has changed due to relative changes in the market value of the constituent securities. b) if tax payments can be minimized. Other implications of EMH are: Price changes are random and unpredictable Investors are not easily fooled by the glossy financial reports or à ¢Ã¢â€š ¬Ã‹Å"creative accounting techniques Timing of new issues of securities are not important since prices represent the intrinsic and will reflect the degree of risk in the share. Thus under EMH neither fundamental nor technical analysis can be used to achieve superior gains. Investors should concentrate on constructing and holding efficiently diversified portfolios. 2.6 Empirical Evidences Based on the literature, it can be seen that there are two competing schools of thoughts about market efficiency. The first school argues that markets are efficient and as a result, returns cannot be predicted. For example early studies (Working, 1934; Kendall, 1943, 1953; Cootner, 1962; Osborne, 1962; Fama, 1965) on developed markets support the weak form efficiency of the market with a low degree of serial correlation and transaction cost. The studies in this school of thought, support the Efficient Market Hypothesis (EMH) and show that price changes could not be used to forecast future price changes, especially after transaction costs were taken into account. The second school, on the other hand, provides empirical evidence of à ¢Ã¢â€š ¬Ã‹Å"anomalies that contradict the theory of efficient markets. Some of these studies are Summers (1986), Keim (1988), Fama and French (1988), Lo and MacKinlay (1988) and Poterba and Summers (1988). They found some à ¢Ã¢â€š ¬Ã‹Å"anomalies, which could not be explained by the theory of Fama (1965). Some of the market anomalies that they found are: January Effect/Turn of The Year Effect Stock returns are usually abnormally high during the first few days of January. The January effect occurs because many investors choose to sell some of their stock right before the end of the year in order to claim a capital loss for tax purposes. Then they quickly reinvest their money after the new year, causing stock prices to rise. Rozeff and Kinney (1976) was among the first to prove this market anomaly. Rozeff and Kinney (1976) methodology gives smaller companies greater relative influence than would be true in value-weighted indices where large firms dominate. Subsequent researches (Reinganum, 1983; Roll, 1983, among others) later confirm that the January effect is a small cap phenomenon. Size Effect/Small Firm Effect The Size Effect is the tendency for firms with a small market capitalization to outperform larger companies over the long term. For example Banz (1981) and Reinganum (1981) showed that small-capitalization firms on the New York Stock Exchange (NYSE) earned a return in excess of what would be predicted by the Sharpe (1964) Linter (1965) capital asset-pricing model (CAPM) from 1936-1975. However as mentioned by G.W. Schwert (2003, p.943), it seems that the small-firm anomaly has disappeared since the initial publication of the papers that discovered it. Alternatively, the differential risk premium for small-capitalization stocks has decreased over the years. Weekend Effect/Day of The Week Effect This is a phenomenon in which stock returns on Mondays are often significantly lower than those of the immediately preceding Friday. French (1890) observed this anomaly. He noted that the average return to the Standard and Poors (SP) Composite Portfolio was reliably negative over weekends in the periods 1953-1977. Again, like the size effect, the weekend effect seems to have disappeared, or at least substantially attenuated, since it was first documented in 1980. Value Effect/Price Earnings Ratio Effect The value effect refers to the tendency for stocks with low price earnings ratio to outperform portfolios consisting of stocks with a high price earnings ratio. Basu (1977) shows that investors holding low price earnings ratio portfolio earned higher returns. The existence of market anomalies have important implications. If stock returns do not follow a random process, then it is possible to design profitable trading strategies based on historical information 2.6.1 Empirical Evidences from Developing Countries Despite the large number of empirical studies that have been conducted to test the validity of the Efficient Market Hypothesis (EMH) in developed countries with booming financial markets, studies to support or dispute the efficiency or inefficiency of the African stock markets are quite limited. There is a small number of empirical studies analyzing emerging African equity markets with regards to weak form of market efficiency test. While some of these studies have analysed single markets ( e.g. Samuels and Yacout 1981; Parkinson 1984; Ayadi 1984; Dickinson and Muragu 1994; Osei 1998; Olowe 1999; Mecagni and Sourial 1999; Asal 2000; Adelegan, 2004; Dewotor and Gborglah, 2004; Ntim et al., 2007), others have analysed groups of countries (e.g. Claessens et al., 1995; Magnusson and Wydick, 2002; Smith et al., 2002; Appiah-Kusi and Menya, 2003; Simons and Laryea, 2004; Jefferis and Smith, 2005). However, while there are only a few empirical studies, their conclusions as to the efficiency and predictability of future stock returns have been mixed. For example Dickinson and Muragu (1994) shows that the Kenyan stock market is weak form efficient, in contrast to the results of Parkinson (1984). Also, most of the existing studies made use of conventional weak form testing techniques such as serial correlation tests. Samuels and Yacout (1981) and Parkinson (1984) were among the first to use serial correlation tests to examine the weak form efficiency on the African continent. Samuels and Yacout analysed the weak form market efficiency in weekly price series of 21 listed Nigerian firms from 1977 to 1979 and provided empirical evidence that the market was efficient. Parkinson on his part, analysed monthly price series of 30 listed Kenyan firms from 1974 to 1978 and rejected the weak form efficiency. Dickinson and Muragu (1994) reinvestigated the Kenyan market by applying run and serial correlation tests to weekly stock price series of 30 listed companies on the Nairobi Stock Exchange and their results were in contrast with Parkinson (1984). They demonstrated that successive price changes are independent of each other for the majority of the companies investigated. Most of the developing countries suffer from the problem of thin trading (Mlambo and Biekpe, 2005). The problems caused by thin trading have been widely acknowledged in financial market researches (e.g., Dimson, 1979; Cohen et al. ,1983; Butler and Simonds, 1987; Lo and Mackinlay, 1990a and b; Bowie, 1994; Muthuswamy and Whaley, 1994) . Fisher (1966) who was the first to identify the bias caused by thin trading in the serial correlation of index returns, explained that recorded prices of securities are not necessarily equal to their underlying theoretical values. This is because when a share does not trade, the price recorded remains the closing price when the share was last traded. However, while most of the African stock markets suffer from thin trading, many existing studies fail to adjust for thin trading. For example recent studies conducted on the Stock Exchange of Mauritius (Appiah-Kusi and Menya, 2003 and Simons and Laryes, 2004) made used of conventional techniques and did not adjust for thin trading. Other studies (Kabba, 1998; Roux and Gilberson, 1978 and Poshawale, 1996) which have examined the behavior of stock price and rejected the weak-form efficiency, have explained that the inefficiency might be due to delay in operations and high transaction cost, thinness of trading and illiquidity in the market.